Microsoft creates industry standards for datacenter hardware storage and security
Today we are announcing a next-generation specification for solid state device (SSD) storage, Project Denali. We’re also discussing Project Cerberus, which provides a critical component for security protection that to date has been missing from server hardware: protection, detection and recovery from attacks on platform firmware. Both storage and security are the next frontiers for hardware innovation, and today we’re highlighting the latest advancements across these key focus areas to further the industry in enabling the future of the cloud. Storage paradigms have performed well on-premises, but they haven’t resulted in innovation for increasing performance and cost efficiencies needed for cloud-based models. For this reason, we’re setting out to define a new standard for flash storage specifically targeted for cloud-based workloads and I’m excited to reveal Project Denali, which we’re establishing with CNEX Labs. Fundamentally, Project Denali standardizes the SSD firmware interfaces by disaggregating the functionality for software-defined data layout and media management. With Project Denali, customers can achieve greater levels of performance, while leveraging the cost-reduction economics that come at cloud scale. Read about it in the Azure blog.Enhance Azure SQL Data Warehouse performance with new monitoring functionality for Columnstore
Azure SQL Data Warehouse (SQL DW) is a SQL-based petabyte-scale, massively parallel, cloud solution for data warehousing. It is fully managed and highly elastic, enabling you to provision and scale capacity in minutes. You can scale compute and storage independently, allowing you to range from burst to archival scenarios. Azure SQL DW is powered by a Columnstore engine to provide super-fast performance for analytic workloads. This is the same Columnstore engine that is built into the industry leading SQL Server Database from Microsoft. To get full speed from the Azure SQL DW, it is important to maximize Columnstore Row Group quality. A row group is the chunk of rows that are compressed together in the Columnstore. In order to enable easier monitoring and tuning of row group quality we are now exposing a new Dynamic Management View (DMV). Read about it on the Azure blog.Azure SQL Data Warehouse now supports automatic creation of statistics
We are pleased to announce that Azure SQL Data Warehouse (Azure SQL DW) now supports automatic creation of column level statistics. Azure SQL DW is a fast, flexible, and secure analytics platform for the enterprise. Modern systems such as Azure SQL DW, rely on cost-based optimizers to generate quality execution plans for user queries. Even though Azure SQL DW implements a cost-based optimizer, the system relies on developers and administrators to create statistics objects manually. When all queries are known in advance, determining what statistics objects need to be created is an achievable task. However, when the system is faced with ad-hoc and random queries which is typical for the data warehousing workloads, system administrators may struggle to predict what statistics need to be created leading to potentially suboptimal query execution plans and longer query response times. One way to mitigate this problem is to create statistics objects on all the table columns in advance. However, that process comes with a penalty as statistics objects need to be maintained during table loading process, causing longer loading times. Read about it in the Azure blog.
